A non-Newtonian gradient for contour detection in images with multiplicative noise
In this paper, a new operator for contour detection in images with multiplicative noise is presented. Traditional methods of edge detection, as those based in gradient operator or measures of variance, follow a logic and a math formulation in correspondence with the Differential and Integral Calculu...
| Autor Principal: | Mora, Marco |
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| Otros Autores: | Cordova-Lepe, Fernando, Del Valle-Salamanca, Rodrigo |
| Formato: | Artículo |
| Idioma: | English |
| Publicado: |
2017
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| Materias: | |
| Acceso en línea: |
http://repositorio.ucm.cl:8080/handle/ucm/1540 |
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| Sumario: |
In this paper, a new operator for contour detection in images with multiplicative noise is presented. Traditional methods of edge detection, as those based in gradient operator or measures of variance, follow a logic and a math formulation in correspondence with the Differential and Integral Calculus of Newton. This work presents a new operator of non-Newtonian type which had shown be more efficient in contour detection than the traditional operators. Like the regular gradient, a non-Newtonian gradient can be used in a number of more complex methods, which shows its potential in the contours detection in images affected by multiplicative noise. |
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